Meanwhile, NAS is prohibitively costly. The computational intensity of single-task NAS can be discouraging, not to mention cross-task NAS experiments. To solve this computation limitation, NAS-Bench-101 [1]} and NAS-Bench-201 [2]} were proposed. These benchmarks have offered great values for the NAS community, but we believe the research scope of NAS can be further enlarged beyond classification problems and cell-based search spaces. To avoid confusion, throughout this paper we use dataset to refer to a set of original images, and task for pointing to certain vision domain. Hence, there can be multiple tasks for one dataset (e.g., COCO detection and segmentation).
